diff --git a/Project.toml b/Project.toml
index f92439e5..1b3671a8 100644
--- a/Project.toml
+++ b/Project.toml
@@ -11,6 +11,7 @@ NLPModels = "a4795742-8479-5a88-8948-cc11e1c8c1a6"
 NLPModelsModifiers = "e01155f1-5c6f-4375-a9d8-616dd036575f"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 SolverCore = "ff4d7338-4cf1-434d-91df-b86cb86fb843"
+SolverParameters = "d076d87d-d1f9-4ea3-a44b-64b4cdd1e470"
 SolverTools = "b5612192-2639-5dc1-abfe-fbedd65fab29"
 
 [compat]
@@ -19,6 +20,7 @@ LinearOperators = "2.0"
 NLPModels = "0.21"
 NLPModelsModifiers = "0.7"
 SolverCore = "0.3"
+SolverParameters = "0.1"
 SolverTools = "0.9"
 julia = "1.6"
 
diff --git a/src/JSOSolvers.jl b/src/JSOSolvers.jl
index 9cc4703c..07329a86 100644
--- a/src/JSOSolvers.jl
+++ b/src/JSOSolvers.jl
@@ -4,7 +4,7 @@ module JSOSolvers
 using LinearAlgebra, Logging, Printf
 
 # JSO packages
-using Krylov, LinearOperators, NLPModels, NLPModelsModifiers, SolverCore, SolverTools
+using Krylov, LinearOperators, NLPModels, NLPModelsModifiers, SolverCore, SolverParameters, SolverTools
 
 import SolverCore.solve!
 export solve!
diff --git a/src/lbfgs.jl b/src/lbfgs.jl
index c5211d9a..4d41e4c2 100644
--- a/src/lbfgs.jl
+++ b/src/lbfgs.jl
@@ -1,5 +1,37 @@
 export lbfgs, LBFGSSolver
 
+"""
+    LbfgsParameterSet{T} <: AbstractParameterSet
+
+This structure designed for `lbfgs` regroups the following parameters:
+  - mem::Parameter{Int, IntegerRange{Int}}: memory parameter of the `lbfgs` algorithm
+  - τ₁::Parameter{T, RealInterval{T}}: slope factor in the Wolfe condition when performing the line search
+  - bk_max::Parameter{Int, IntegerRange{Int}}: maximum number of backtracks when performing the line search.
+
+  Default values are:
+  - `mem::Int = 5`
+  - `τ₁::T = T(0.9999)`
+  - `bk_max:: Int = 25`
+"""
+struct LbfgsParameterSet{T} <: AbstractParameterSet
+  mem::Parameter{Int, IntegerRange{Int}}
+  τ₁::Parameter{T, RealInterval{T}}
+  bk_max::Parameter{Int, IntegerRange{Int}}
+end
+
+# add a default constructor
+function LbfgsParameterSet{T}(; mem::Int = 5, τ₁::T = T(0.9999), bk_max::Int = 25) where {T}
+  LbfgsParameterSet(
+    Parameter(mem, IntegerRange(Int(5), Int(20))),
+    Parameter(
+      τ₁,
+      RealInterval(T(0), T(1), lower_open = true),
+    ),
+    Parameter(bk_max, IntegerRange(Int(1), Int(100))),
+  )
+end
+LbfgsParameterSet(mem::Int, τ₁::T, bk_max::Int) where {T} = LbfgsParameterSet{T}(mem = mem, τ₁ = τ₁, bk_max = bk_max)
+
 """
     lbfgs(nlp; kwargs...)
 
@@ -62,10 +94,15 @@ mutable struct LBFGSSolver{T, V, Op <: AbstractLinearOperator{T}, M <: AbstractN
   d::V
   H::Op
   h::LineModel{T, V, M}
+  params::LbfgsParameterSet{T}
 end
 
-function LBFGSSolver(nlp::M; mem::Int = 5) where {T, V, M <: AbstractNLPModel{T, V}}
+function LBFGSSolver(nlp::M; kwargs...) where {T, V, M <: AbstractNLPModel{T, V}}
   nvar = nlp.meta.nvar
+
+  params = LbfgsParameterSet{T}(; kwargs...)
+  mem = value(params.mem)
+
   x = V(undef, nvar)
   d = V(undef, nvar)
   xt = V(undef, nvar)
@@ -74,7 +111,7 @@ function LBFGSSolver(nlp::M; mem::Int = 5) where {T, V, M <: AbstractNLPModel{T,
   H = InverseLBFGSOperator(T, nvar, mem = mem, scaling = true)
   h = LineModel(nlp, x, d)
   Op = typeof(H)
-  return LBFGSSolver{T, V, Op, M}(x, xt, gx, gt, d, H, h)
+  return LBFGSSolver{T, V, Op, M}(x, xt, gx, gt, d, H, h, params)
 end
 
 function SolverCore.reset!(solver::LBFGSSolver)
@@ -88,12 +125,14 @@ function SolverCore.reset!(solver::LBFGSSolver, nlp::AbstractNLPModel)
 end
 
 @doc (@doc LBFGSSolver) function lbfgs(
-  nlp::AbstractNLPModel;
+  nlp::AbstractNLPModel{T, V};
   x::V = nlp.meta.x0,
   mem::Int = 5,
+  τ₁::T = T(0.9999),
+  bk_max::Int = 25,
   kwargs...,
-) where {V}
-  solver = LBFGSSolver(nlp; mem = mem)
+) where {T, V}
+  solver = LBFGSSolver(nlp; mem = mem, τ₁ = τ₁, bk_max = bk_max)
   return solve!(solver, nlp; x = x, kwargs...)
 end
 
@@ -108,8 +147,6 @@ function SolverCore.solve!(
   max_eval::Int = -1,
   max_iter::Int = typemax(Int),
   max_time::Float64 = 30.0,
-  τ₁::T = T(0.9999),
-  bk_max::Int = 25,
   verbose::Int = 0,
   verbose_subsolver::Int = 0,
 ) where {T, V}
@@ -124,6 +161,10 @@ function SolverCore.solve!(
   start_time = time()
   set_time!(stats, 0.0)
 
+  # parameters
+  τ₁ = value(solver.params.τ₁)
+  bk_max = value(solver.params.bk_max)
+
   n = nlp.meta.nvar
 
   solver.x .= x